activity
20202026
most citedRU-Net: Regularized Unrolling Network for Scene Graph Generation

3 citations · 5 across the 3 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

Local Margin Restoration for Test-Time Adaptation of Vision-Language Models

Yan Huang, Guowei Wang, Xu Wang +2

Vision-language models (VLMs) such as CLIP exhibit remarkable zero-shot capabilities, yet their performance frequently degrades sharply under unexpected test-time distribution shif…

cs.CV2025

SGC-Net: Stratified Granular Comparison Network for Open-Vocabulary HOI Detection

Xin Lin, Chong Shi, Zuopeng Yang +2

Recent open-vocabulary human-object interaction (OV-HOI) detection methods primarily rely on large language model (LLM) for generating auxiliary descriptions and leverage knowledge…

cs.CV2025

Distraction is All You Need for Multimodal Large Language Model Jailbreaking

Zuopeng Yang, Jiluan Fan, Anli Yan +5

Multimodal Large Language Models (MLLMs) bridge the gap between visual and textual data, enabling a range of advanced applications. However, complex internal interactions among vis…

cs.CV20222 cited

HL-Net: Heterophily Learning Network for Scene Graph Generation

Xin Lin, Changxing Ding, Yibing Zhan +2

Scene graph generation (SGG) aims to detect objects and predict their pairwise relationships within an image. Current SGG methods typically utilize graph neural networks (GNNs) to…

cs.CV20223 cited

RU-Net: Regularized Unrolling Network for Scene Graph Generation

Xin Lin, Changxing Ding, Jing Zhang +2

Scene graph generation (SGG) aims to detect objects and predict the relationships between each pair of objects. Existing SGG methods usually suffer from several issues, including 1…

cs.CV2020

GPS-Net: Graph Property Sensing Network for Scene Graph Generation

Xin Lin, Changxing Ding, Jinquan Zeng +1

Scene graph generation (SGG) aims to detect objects in an image along with their pairwise relationships. There are three key properties of scene graph that have been underexplored…